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Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/97661, first published .
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Quantifying the Impact of Anonymization-Induced Clinical Data Quality Loss: Methodological Quantitative Case Study Using Primary Diagnosis Codes and Hospital Length of Stay

Quantifying the Impact of Anonymization-Induced Clinical Data Quality Loss: Methodological Quantitative Case Study Using Primary Diagnosis Codes and Hospital Length of Stay

Gaetan Kamdje Wabo   1 , MSc ;   Piotr Pawel Sokolowski   1 , MD ;   Mahboubeh Jannesari Ladani   1 , MSc ;   Michael Hagmann   1 , PhD ;   Thomas Ganslandt   2 , MD ;   Fabian Siegel   1 , MD

1 Department of Biomedical Informatics, Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany

2 Institute of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Bavaria, Germany

Corresponding Author:

  • Gaetan Kamdje Wabo, MSc
  • Department of Biomedical Informatics
  • Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, University of Heidelberg
  • Theodor-Kutzer-Ufer 1–3, House 3, Floor 4
  • Mannheim 68167
  • Germany
  • Phone: 49 621 383 8088
  • Email: gaetankamdje.wabo@medma.uni-heidelberg.de